Dynamic Modeling of the Da Vinci Research Kit Arm for the Estimation of Interaction Wrench

The commercialized version of the da Vinci robot currently lacks of the haptic feedback to the master arm. Thus, the surgeon has no haptic sense and relies only on the visual feedback. For this reason, in the recent research activities using the da Vinci Research Kit (dVRK) platform, the reflection of the interaction force between the slave tool and the environment to the master manipulator is a topic of high interest. In this work a sensorless model-based approach for contact force and torque estimation is presented and validated. The dynamics of the dVRK slave arm is modeled and its parameters are identified. The idea is to use the joint torques obtained from the measured motor currents and to subtract the torques resulting from the dynamics of the robot arm. The resulting torques are therefore only due to the external forces and torques acting on the tool, which are then obtained through the inverse transpose of the Jacobian matrix. The accuracy of this method is assessed by comparing the estimated wrench to the one measured by a force$/$torque sensor (ATI mini 45). It is shown that the external wrench is well estimated compared to the measured one.

[1]  Emmanuel Wilson,et al.  External force estimation and implementation in robotically assisted minimally invasive surgery , 2017, The international journal of medical robotics + computer assisted surgery : MRCAS.

[2]  G. Oriolo,et al.  Robotics: Modelling, Planning and Control , 2008 .

[3]  Jan Swevers,et al.  Optimal robot excitation and identification , 1997, IEEE Trans. Robotics Autom..

[4]  Giuseppe Carlo Calafiore,et al.  Robot Dynamic Calibration: Optimal Excitation Trajectories and Experimental Parameter Estimation , 2001 .

[5]  J. S.,et al.  EXPERIMENTAL ROBOT IDENTIFICATION USING OPTIMISED PERIODIC TRAJECTORIES , 1996 .

[6]  M. Gautier Numerical calculation of the base inertial parameters of robots , 1991, J. Field Robotics.

[7]  Rui Pedro Duarte Cortesão,et al.  SageRobotics: open source framework for symbolic computation of robot models , 2012, SAC '12.

[8]  Peter Kazanzides,et al.  An open-source research kit for the da Vinci® Surgical System , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[9]  D. Yuh,et al.  Effects of visual force feedback on robot-assisted surgical task performance. , 2008, The Journal of thoracic and cardiovascular surgery.

[10]  Rui Pedro Duarte Cortesão,et al.  Physical feasibility of robot base inertial parameter identification: A linear matrix inequality approach , 2014, Int. J. Robotics Res..

[11]  Dale A. Lawrence Stability and transparency in bilateral teleoperation , 1993, IEEE Trans. Robotics Autom..

[12]  Christopher R. Wagner,et al.  Force Feedback Benefit Depends on Experience in Multiple Degree of Freedom Robotic Surgery Task , 2007, IEEE Transactions on Robotics.

[13]  Warren S. Grundfest,et al.  A tactile feedback system for robotic surgery , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[14]  Allison M. Okamura,et al.  Methods for haptic feedback in teleoperated robot-assisted surgery , 2004 .

[15]  Allison M. Okamura,et al.  Analysis of Suture Manipulation Forces for Teleoperation with Force Feedback , 2002, MICCAI.

[16]  Philip E. Gill,et al.  Numerical Linear Algebra and Optimization , 1991 .

[17]  Anders Robertsson,et al.  Robotic force estimation using motor torques and modeling of low velocity friction disturbances , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[18]  Bernhard Kübler,et al.  Prototype of Instrument for Minimally Invasive Surgery with 6-Axis Force Sensing Capability , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[19]  Russell H. Taylor,et al.  Medical robotics in computer-integrated surgery , 2003, IEEE Trans. Robotics Autom..

[20]  Russell H. Taylor,et al.  Medical robotics in computer-integrated surgery , 2003, IEEE Trans. Robotics Autom..

[21]  Bruno Siciliano,et al.  Modelling and identification of the da Vinci Research Kit robotic arms , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[22]  Mahdi Tavakoli,et al.  A force reflective master-slave system for minimally invasive surgery , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[23]  Wisama Khalil,et al.  Direct calculation of minimum set of inertial parameters of serial robots , 1990, IEEE Trans. Robotics Autom..

[24]  Bruno Siciliano,et al.  A novel force sensing integrated into the trocar for minimally invasive robotic surgery , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[25]  Allison M. Okamura,et al.  Force Feedback and Sensory Substitution for Robot-Assisted Surgery , 2011 .

[26]  Allison M. Okamura,et al.  Force-Feedback Surgical Teleoperator: Controller Design and Palpation Experiments , 2008, 2008 Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems.

[27]  Rajnikant V. Patel,et al.  Robot-assisted Tactile Sensing for Minimally Invasive Tumor Localization , 2009, Int. J. Robotics Res..

[28]  Septimiu E. Salcudean,et al.  Bimanual telerobotic surgery with asymmetric force feedback: A daVinci® surgical system implementation , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.